1. Field of the Invention
The following description relates to an image processing method and image processing apparatus, for example, an image processing method which may obtain clear images using a time axis low band pass filter, and an image processing apparatus thereof.
2. Description of Related Art
As illustrated in FIG. 1, an electron microscope generates a scan electron beam of XV direction in an electron gun 1, and irradiates the electron beam to a sample 2 placed on a lower portion of an evacuated chamber 10. An electron returning from the sample to which the electron beam is irradiated is detected by a highly sensitive sensor PMT (3: photomultiplier tube), and a weak second electron is amplified. The amplified second electron passes an AD converter (ADC) and is accumulated in a memory as image data, and the created image is transmitted to a control computer and is displayed on a monitor 40. A user becomes able to check the monitor and find or analyze a defect of a surface of the sample such as a wafer.
An image processing apparatus is an essential apparatus attached to such an electron microscope or a 3 dimensional focused ion-beam lithography etc. An image processing apparatus generates signals controlling electron beams and forms images of samples. It is the most important element in an electron microscope, or a 3 dimensional focused ion-beam apparatus where high resolution and quality image is an important function.
A conventional image processing apparatus obtains one image by consecutively expressing a signal of a secondary electron detected by a PMT, and sequentially obtains a total of N number of images in the same method.
Such an image consists of a same size and same number of pixels regarding a same object. However, in the process of creating an image as illustrated in FIG. 2 where grey level values (dotted line graph in FIG. 2) of the same location pixel of 128 image data are sequentially generated, noise occurs due to electrical or mechanical vibration, and thus the grey level values of the pixels in the same location are not identical. And in the case of creating an image of a sample by simply combining such N number of images, it is impossible to generate an exact image of the sample as illustrated in FIG. 3.
Therefore, in most commercial products, an image including noise is converted into a high quality image through an after-process, wherein the most frequently used method is the moving average filter method.
The moving average filter method is a method of averaging the grey values of the pixels in the same location in N number of images to form one integrated image using the average value. In the case of performing such an after-process, it is possible to obtain clearer images than those obtained when just combining N number of images as illustrated in FIG. 4.
An image which has been after-processed by the moving average filter method is clearer than an image which has not been after-processed, but there is a problem that, when the image shakes in X and Y directions due to mechanical vibration, boundary lines are averaged and thus edges become unclear and the image appears somewhat murky.